Evaluating the logistic mixture model on real and simulated TG curves View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-01

AUTHORS

F. Barbadillo, A. Fuentes, S. Naya, R. Cao, J. L. Mier, R. Artiaga

ABSTRACT

The aim of this paper is to evaluate and explain the fitting of dynamic TG curves by a mixture of logistic functions. This model assumes that more than one physical process may be involved in each mass loss step and that each physical process may extend along all the experiment. One of the main sources of difficulties in TG is that, very often, different stages of decomposition substantially overlap each other. Several real and simulated TG curves were analysed in this paper. An optimal fitting of the TG curves was obtained by a mixture of logistics. In many cases the optimal fitting reproduces accurately the TG curve. Accordingly, the TG curve can be understood as a sum of parallel reactions, where each single reaction is represented by one or a small number of logistic components. Additionally, making use of the analytical derivative of the fitting, a mixture of Arrhenius reaction order equations was applied to the same curves. In all the cases, the fitting obtained with the mixture of Arrhenius was worse than the obtained with the mixture of logistics. A software was developed to automatically perform these tasks. The physical meaning of the fitting was explained. More... »

PAGES

223-227

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10973-006-8283-x

DOI

http://dx.doi.org/10.1007/s10973-006-8283-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1042964163


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Numerical and Computational Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Department of Industrial\nEngineering II, Escola Polit\u00e9cnica Superior, Universidade\nda Coru\u00f1a, 15403, Ferrol, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Barbadillo", 
        "givenName": "F.", 
        "id": "sg:person.014037013535.67", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014037013535.67"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Department of Industrial\nEngineering II, Escola Polit\u00e9cnica Superior, Universidade\nda Coru\u00f1a, 15403, Ferrol, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fuentes", 
        "givenName": "A.", 
        "id": "sg:person.015431754535.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015431754535.33"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Department of Mathematics, Faculty of Computer Sciences, Universidade da Coru\u00f1a, 15071, A Coru\u00f1a, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Naya", 
        "givenName": "S.", 
        "id": "sg:person.010043463111.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010043463111.42"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Department of Mathematics, Faculty of Computer Sciences, Universidade da Coru\u00f1a, 15071, A Coru\u00f1a, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cao", 
        "givenName": "R.", 
        "id": "sg:person.014342627627.01", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014342627627.01"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Department of Industrial\nEngineering II, Escola Polit\u00e9cnica Superior, Universidade\nda Coru\u00f1a, 15403, Ferrol, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mier", 
        "givenName": "J. L.", 
        "id": "sg:person.010034664231.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010034664231.04"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of A Coru\u00f1a", 
          "id": "https://www.grid.ac/institutes/grid.8073.c", 
          "name": [
            "Department of Industrial\nEngineering II, Escola Polit\u00e9cnica Superior, Universidade\nda Coru\u00f1a, 15403, Ferrol, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Artiaga", 
        "givenName": "R.", 
        "id": "sg:person.011361512031.23", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011361512031.23"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1023/a:1021697128851", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001519734", 
          "https://doi.org/10.1023/a:1021697128851"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/app.2288", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002865256"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/polc.5070060121", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006272115"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/polc.5070060121", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006272115"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1246/bcsj.38.1881", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007444724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.polymdegradstab.2004.03.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010700345"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0040-6031(00)00443-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014383963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0040-6031(92)85123-d", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016609775"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0040-6031(84)85029-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019981902"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0040-6031(99)00253-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022341351"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1011573218107", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043313017", 
          "https://doi.org/10.1023/a:1011573218107"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bfb0099519", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051486155", 
          "https://doi.org/10.1007/bfb0099519"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2007-01", 
    "datePublishedReg": "2007-01-01", 
    "description": "The aim of this paper is to evaluate and explain the fitting of dynamic TG curves by a mixture of logistic functions. This model assumes that more than one physical process may be involved in each mass loss step and that each physical process may extend along all the experiment. One of the main sources of difficulties in TG is that, very often, different stages of decomposition substantially overlap each other. Several real and simulated TG curves were analysed in this paper. An optimal fitting of the TG curves was obtained by a mixture of logistics. In many cases the optimal fitting reproduces accurately the TG curve. Accordingly, the TG curve can be understood as a sum of parallel reactions, where each single reaction is represented by one or a small number of logistic components. Additionally, making use of the analytical derivative of the fitting, a mixture of Arrhenius reaction order equations was applied to the same curves. In all the cases, the fitting obtained with the mixture of Arrhenius was worse than the obtained with the mixture of logistics. A software was developed to automatically perform these tasks. The physical meaning of the fitting was explained.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10973-006-8283-x", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1294862", 
        "issn": [
          "1388-6150", 
          "1572-8943"
        ], 
        "name": "Journal of Thermal Analysis and Calorimetry", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "87"
      }
    ], 
    "name": "Evaluating the logistic mixture model on real and simulated TG curves", 
    "pagination": "223-227", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "cca71d9a15be327c76985f1834de3026000fe9c82df8eb29d0a0ec237ae4fe5b"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10973-006-8283-x"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1042964163"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10973-006-8283-x", 
      "https://app.dimensions.ai/details/publication/pub.1042964163"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T15:02", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8663_00000515.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs10973-006-8283-x"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10973-006-8283-x'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10973-006-8283-x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10973-006-8283-x'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10973-006-8283-x'


 

This table displays all metadata directly associated to this object as RDF triples.

133 TRIPLES      21 PREDICATES      38 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10973-006-8283-x schema:about anzsrc-for:01
2 anzsrc-for:0103
3 schema:author N727c9f6a69f04233aa1af507a13ac39b
4 schema:citation sg:pub.10.1007/bfb0099519
5 sg:pub.10.1023/a:1011573218107
6 sg:pub.10.1023/a:1021697128851
7 https://doi.org/10.1002/app.2288
8 https://doi.org/10.1002/polc.5070060121
9 https://doi.org/10.1016/0040-6031(84)85029-7
10 https://doi.org/10.1016/0040-6031(92)85123-d
11 https://doi.org/10.1016/j.polymdegradstab.2004.03.006
12 https://doi.org/10.1016/s0040-6031(00)00443-3
13 https://doi.org/10.1016/s0040-6031(99)00253-1
14 https://doi.org/10.1246/bcsj.38.1881
15 schema:datePublished 2007-01
16 schema:datePublishedReg 2007-01-01
17 schema:description The aim of this paper is to evaluate and explain the fitting of dynamic TG curves by a mixture of logistic functions. This model assumes that more than one physical process may be involved in each mass loss step and that each physical process may extend along all the experiment. One of the main sources of difficulties in TG is that, very often, different stages of decomposition substantially overlap each other. Several real and simulated TG curves were analysed in this paper. An optimal fitting of the TG curves was obtained by a mixture of logistics. In many cases the optimal fitting reproduces accurately the TG curve. Accordingly, the TG curve can be understood as a sum of parallel reactions, where each single reaction is represented by one or a small number of logistic components. Additionally, making use of the analytical derivative of the fitting, a mixture of Arrhenius reaction order equations was applied to the same curves. In all the cases, the fitting obtained with the mixture of Arrhenius was worse than the obtained with the mixture of logistics. A software was developed to automatically perform these tasks. The physical meaning of the fitting was explained.
18 schema:genre research_article
19 schema:inLanguage en
20 schema:isAccessibleForFree false
21 schema:isPartOf Nb43728b2ebd34dcea3e799d753ec7859
22 Nb95e8c4534ba427b9aa65b3e97161664
23 sg:journal.1294862
24 schema:name Evaluating the logistic mixture model on real and simulated TG curves
25 schema:pagination 223-227
26 schema:productId N639ea13c682c45aaaa4274d3f422682f
27 N67ad533a8567402fb4c06fdb310e153b
28 N9abad2ffc77346dda1a3f417b1cabc41
29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042964163
30 https://doi.org/10.1007/s10973-006-8283-x
31 schema:sdDatePublished 2019-04-10T15:02
32 schema:sdLicense https://scigraph.springernature.com/explorer/license/
33 schema:sdPublisher N15f74514193140289e09538f14478170
34 schema:url http://link.springer.com/10.1007%2Fs10973-006-8283-x
35 sgo:license sg:explorer/license/
36 sgo:sdDataset articles
37 rdf:type schema:ScholarlyArticle
38 N0c4321641a4b4e9e8c23c76e813cf924 rdf:first sg:person.015431754535.33
39 rdf:rest Nd377af6aec1646b498d59ee342d46c20
40 N15f74514193140289e09538f14478170 schema:name Springer Nature - SN SciGraph project
41 rdf:type schema:Organization
42 N639ea13c682c45aaaa4274d3f422682f schema:name doi
43 schema:value 10.1007/s10973-006-8283-x
44 rdf:type schema:PropertyValue
45 N67663315e432458382eb0365182e0839 rdf:first sg:person.010034664231.04
46 rdf:rest Nd77dbe6df7e14ec3b2b0ddca63da01cb
47 N67ad533a8567402fb4c06fdb310e153b schema:name readcube_id
48 schema:value cca71d9a15be327c76985f1834de3026000fe9c82df8eb29d0a0ec237ae4fe5b
49 rdf:type schema:PropertyValue
50 N727c9f6a69f04233aa1af507a13ac39b rdf:first sg:person.014037013535.67
51 rdf:rest N0c4321641a4b4e9e8c23c76e813cf924
52 N9abad2ffc77346dda1a3f417b1cabc41 schema:name dimensions_id
53 schema:value pub.1042964163
54 rdf:type schema:PropertyValue
55 Nb43728b2ebd34dcea3e799d753ec7859 schema:issueNumber 1
56 rdf:type schema:PublicationIssue
57 Nb95e8c4534ba427b9aa65b3e97161664 schema:volumeNumber 87
58 rdf:type schema:PublicationVolume
59 Nc9943f8507d6484bbbe24a20479569a8 rdf:first sg:person.014342627627.01
60 rdf:rest N67663315e432458382eb0365182e0839
61 Nd377af6aec1646b498d59ee342d46c20 rdf:first sg:person.010043463111.42
62 rdf:rest Nc9943f8507d6484bbbe24a20479569a8
63 Nd77dbe6df7e14ec3b2b0ddca63da01cb rdf:first sg:person.011361512031.23
64 rdf:rest rdf:nil
65 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
66 schema:name Mathematical Sciences
67 rdf:type schema:DefinedTerm
68 anzsrc-for:0103 schema:inDefinedTermSet anzsrc-for:
69 schema:name Numerical and Computational Mathematics
70 rdf:type schema:DefinedTerm
71 sg:journal.1294862 schema:issn 1388-6150
72 1572-8943
73 schema:name Journal of Thermal Analysis and Calorimetry
74 rdf:type schema:Periodical
75 sg:person.010034664231.04 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
76 schema:familyName Mier
77 schema:givenName J. L.
78 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010034664231.04
79 rdf:type schema:Person
80 sg:person.010043463111.42 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
81 schema:familyName Naya
82 schema:givenName S.
83 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010043463111.42
84 rdf:type schema:Person
85 sg:person.011361512031.23 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
86 schema:familyName Artiaga
87 schema:givenName R.
88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011361512031.23
89 rdf:type schema:Person
90 sg:person.014037013535.67 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
91 schema:familyName Barbadillo
92 schema:givenName F.
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014037013535.67
94 rdf:type schema:Person
95 sg:person.014342627627.01 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
96 schema:familyName Cao
97 schema:givenName R.
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014342627627.01
99 rdf:type schema:Person
100 sg:person.015431754535.33 schema:affiliation https://www.grid.ac/institutes/grid.8073.c
101 schema:familyName Fuentes
102 schema:givenName A.
103 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015431754535.33
104 rdf:type schema:Person
105 sg:pub.10.1007/bfb0099519 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051486155
106 https://doi.org/10.1007/bfb0099519
107 rdf:type schema:CreativeWork
108 sg:pub.10.1023/a:1011573218107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043313017
109 https://doi.org/10.1023/a:1011573218107
110 rdf:type schema:CreativeWork
111 sg:pub.10.1023/a:1021697128851 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001519734
112 https://doi.org/10.1023/a:1021697128851
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1002/app.2288 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002865256
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1002/polc.5070060121 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006272115
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1016/0040-6031(84)85029-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019981902
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1016/0040-6031(92)85123-d schema:sameAs https://app.dimensions.ai/details/publication/pub.1016609775
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1016/j.polymdegradstab.2004.03.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010700345
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/s0040-6031(00)00443-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014383963
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/s0040-6031(99)00253-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022341351
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1246/bcsj.38.1881 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007444724
129 rdf:type schema:CreativeWork
130 https://www.grid.ac/institutes/grid.8073.c schema:alternateName University of A Coruña
131 schema:name Department of Industrial Engineering II, Escola Politécnica Superior, Universidade da Coruña, 15403, Ferrol, Spain
132 Department of Mathematics, Faculty of Computer Sciences, Universidade da Coruña, 15071, A Coruña, Spain
133 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...